Job Scheduling Strategies for Parallel Processing: 13th International Workshop, JSSPP 2007, Seattle, WA, USA, June 17, 2007. Revised Papers

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Edition: 1

Series: Lecture Notes in Computer Science 4942

ISBN: 3540786988, 9783540786986

Size: 5 MB (5130474 bytes)

Pages: 189/194

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Eitan Frachtenberg, Uwe Schwiegelshohn (auth.), Eitan Frachtenberg, Uwe Schwiegelshohn (eds.)3540786988, 9783540786986

This book constitutes the thoroughly refereed post-workshop proceedings of the 13th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2007, held in Seattle, WA, USA, in June 2007, in conjunction with the 21st ACM International Conference on Supercomputing, ICS 2007.

The 10 revised full research papers presented went through the process of strict reviewing and subsequent improvement. The papers cover all current issues of job scheduling strategies for parallel processing from the supercomputer-centric viewpoint but also address many nontraditional high-performance computing and parallel environments that cannot or need not access a traditional supercomputer, such as grids, Web services, and commodity parallel computers. The papers are organized in topical sections on performance and tools, queueing systems, as well as grid and heterogeneous architectures.


Table of contents :
Front Matter….Pages –
New Challenges of Parallel Job Scheduling….Pages 1-23
Group-Wise Performance Evaluation of Processor Co-allocation in Multi-cluster Systems….Pages 24-36
Enhancing an Open Source Resource Manager with Multi-core/Multi-threaded Support….Pages 37-50
A Job Self-scheduling Policy for HPC Infrastructures….Pages 51-75
QBETS: Queue Bounds Estimation from Time Series….Pages 76-101
Probabilistic Backfilling….Pages 102-115
Impact of Reservations on Production Job Scheduling….Pages 116-131
Prospects of Collaboration between Compute Providers by Means of Job Interchange….Pages 132-151
GridARS: An Advance Reservation-Based Grid Co-allocation Framework for Distributed Computing and Network Resources….Pages 152-168
A Self-optimized Job Scheduler for Heterogeneous Server Clusters….Pages 169-187
Back Matter….Pages –

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